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Model selection for covariance structures analysis in nursing research

S J Henly1, P E Vermeersch, L J Duckett

  • 1College of Nursing, University of North Dakota, USA.

Western Journal of Nursing Research
|June 6, 1998
PubMed
Summary
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Covariance structures analysis in nursing research uses a model selection approach to identify the best statistical model. This method enhances model interpretability and goodness-of-fit by balancing model misfit and sampling error.

Area of Science:

  • Nursing Research
  • Statistical Modeling
  • Psychometrics

Background:

  • Covariance structures analysis is crucial for modeling complex human health processes in nursing.
  • Existing methods may not adequately balance model fit with parsimony.
  • A need exists for robust model selection strategies in nursing research.

Purpose of the Study:

  • To introduce and evaluate the model selection approach for covariance structures analysis in nursing.
  • To demonstrate how this approach enhances statistical model appraisal.
  • To discuss the implications for theory development and application in nursing.

Main Methods:

  • Utilizing covariance structures analysis with a specific model selection strategy.
  • Evaluating competing theoretical models as approximations.

Related Experiment Videos

  • Applying model selection criteria that consider population misfit and sampling error.

    • Main Results:

    • The model selection approach simultaneously improves parameter interpretability and goodness-of-fit.
    • This method provides a systematic way to choose the "best" approximating model.
    • Effectively balances technical accuracy with theoretical relevance.

    Conclusions:

    • The model selection approach offers significant advantages for covariance structures analysis in nursing.
    • It supports the integration of statistical rigor with theoretical advancement in the field.
    • Recommends this approach for enhancing the quality of nursing research models.